| Year |
Citation |
Score |
| 2023 |
Dax M, Green SR, Gair J, Pürrer M, Wildberger J, Macke JH, Buonanno A, Schölkopf B. Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference. Physical Review Letters. 130: 171403. PMID 37172245 DOI: 10.1103/PhysRevLett.130.171403 |
0.509 |
|
| 2022 |
Deistler M, Macke JH, Gonçalves PJ. Energy-efficient network activity from disparate circuit parameters. Proceedings of the National Academy of Sciences of the United States of America. 119: e2207632119. PMID 36279461 DOI: 10.1073/pnas.2207632119 |
0.677 |
|
| 2022 |
Blum C, Baur D, Achauer LC, Berens P, Biergans S, Erb M, Hömberg V, Huang Z, Kohlbacher O, Liepert J, Lindig T, Lohmann G, Macke JH, Römhild J, Rösinger-Hein C, et al. Personalized neurorehabilitative precision medicine: from data to therapies (MWKNeuroReha) - a multi-centre prospective observational clinical trial to predict long-term outcome of patients with acute motor stroke. Bmc Neurology. 22: 238. PMID 35773640 DOI: 10.1186/s12883-022-02759-2 |
0.472 |
|
| 2021 |
Dax M, Green SR, Gair J, Macke JH, Buonanno A, Schölkopf B. Real-Time Gravitational Wave Science with Neural Posterior Estimation. Physical Review Letters. 127: 241103. PMID 34951790 DOI: 10.1103/PhysRevLett.127.241103 |
0.516 |
|
| 2021 |
Dehnen G, Kehl MS, Darcher A, Müller TT, Macke JH, Borger V, Surges R, Mormann F. Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings. Brain Sciences. 11. PMID 34201115 DOI: 10.3390/brainsci11060761 |
0.738 |
|
| 2020 |
Gonçalves PJ, Lueckmann JM, Deistler M, Nonnenmacher M, Öcal K, Bassetto G, Chintaluri C, Podlaski WF, Haddad SA, Vogels T, Greenberg DS, Macke JH. Training deep neural density estimators to identify mechanistic models of neural dynamics. Elife. 9. PMID 32940606 DOI: 10.7554/Elife.56261 |
0.733 |
|
| 2020 |
René A, Longtin A, Macke JH. Inference of a Mesoscopic Population Model from Population Spike Trains. Neural Computation. 1-51. PMID 32521212 DOI: 10.1162/Neco_A_01292 |
0.43 |
|
| 2020 |
Sekhar S, Ramesh P, Bassetto G, Zrenner E, Macke JH, Rathbun DL. Characterizing Retinal Ganglion Cell Responses to Electrical Stimulation Using Generalized Linear Models. Frontiers in Neuroscience. 14: 378. PMID 32477044 DOI: 10.3389/Fnins.2020.00378 |
0.343 |
|
| 2019 |
Macke JH, Nienborg H. Choice (-history) correlations in sensory cortex: cause or consequence? Current Opinion in Neurobiology. 58: 148-154. PMID 31581052 DOI: 10.1016/j.conb.2019.09.005 |
0.352 |
|
| 2019 |
Barrett DG, Morcos AS, Macke JH. Analyzing biological and artificial neural networks: challenges with opportunities for synergy? Current Opinion in Neurobiology. 55: 55-64. PMID 30785004 DOI: 10.1016/J.Conb.2019.01.007 |
0.333 |
|
| 2018 |
Berens P, Freeman J, Deneux T, Chenkov N, McColgan T, Speiser A, Macke JH, Turaga SC, Mineault P, Rupprecht P, Gerhard S, Friedrich RW, Friedrich J, Paninski L, Pachitariu M, et al. Community-based benchmarking improves spike rate inference from two-photon calcium imaging data. Plos Computational Biology. 14: e1006157. PMID 29782491 DOI: 10.1371/Journal.Pcbi.1006157 |
0.725 |
|
| 2018 |
Lueckmann JM, Macke JH, Nienborg H. Can serial dependencies in choices and neural activity explain choice probabilities? The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. PMID 29440531 DOI: 10.1523/Jneurosci.2225-17.2018 |
0.388 |
|
| 2017 |
Nonnenmacher M, Behrens C, Berens P, Bethge M, Macke JH. Signatures of criticality arise from random subsampling in simple population models. Plos Computational Biology. 13: e1005718. PMID 28972970 DOI: 10.1371/journal.pcbi.1005718 |
0.705 |
|
| 2017 |
Denham S, Poirazi P, De Schutter E, Friston K, Chan HK, Nowotny T, Han D, Hong S, Rosay S, Wernle T, Treves A, Goethals S, Brette R, Van Pottelbergh T, Sepulchre R, ... ... Macke JH, et al. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1 Bmc Neuroscience. 18. DOI: 10.1186/S12868-017-0370-3 |
0.652 |
|
| 2016 |
Schütt HH, Harmeling S, Macke JH, Wichmann FA. Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research. PMID 27013261 DOI: 10.1016/J.Visres.2016.02.002 |
0.616 |
|
| 2015 |
Schütt H, Harmeling S, Macke J, Wichmann F. Psignifit 4: Pain-free Bayesian Inference for Psychometric Functions. Journal of Vision. 15: 474. PMID 26326162 DOI: 10.1167/15.12.474 |
0.535 |
|
| 2015 |
Panzeri S, Macke JH, Gross J, Kayser C. Neural population coding: combining insights from microscopic and mass signals. Trends in Cognitive Sciences. 19: 162-72. PMID 25670005 DOI: 10.1016/J.Tics.2015.01.002 |
0.39 |
|
| 2015 |
Küffner R, Zach N, Norel R, Hawe J, Schoenfeld D, Wang L, Li G, Fang L, Mackey L, Hardiman O, Cudkowicz M, Sherman A, Ertaylan G, Grosse-Wentrup M, Hothorn T, ... ... Macke JH, et al. Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression. Nature Biotechnology. 33: 51-7. PMID 25362243 DOI: 10.1038/Nbt.3051 |
0.509 |
|
| 2015 |
Macke JH, Buesing L, Sahani M. Estimating state and parameters in state space models of spike trains Advanced State Space Methods For Neural and Clinical Data. 137-159. DOI: 10.1017/CBO9781139941433.007 |
0.614 |
|
| 2015 |
Park M, Bohner G, Macke JH. Unlocking neural population non-stationarity using a hierarchical dynamics model Advances in Neural Information Processing Systems. 2015: 145-153. |
0.318 |
|
| 2014 |
Fründ I, Wichmann FA, Macke JH. Quantifying the effect of intertrial dependence on perceptual decisions. Journal of Vision. 14. PMID 24944238 DOI: 10.1167/14.7.9 |
0.599 |
|
| 2014 |
Schütt HH, Harmeling S, Macke JH, Wichmann FA. Pain-free bayesian inference for psychometric functions F1000research. 5: 162-162. DOI: 10.1177/03010066140430S101 |
0.593 |
|
| 2014 |
Archer E, Köster U, Pillow J, Macke JH. Low-dimensional models of neural population activity in sensory cortical circuits Advances in Neural Information Processing Systems. 1: 343-351. |
0.595 |
|
| 2013 |
Haefner RM, Gerwinn S, Macke JH, Bethge M. Inferring decoding strategies from choice probabilities in the presence of correlated variability. Nature Neuroscience. 16: 235-42. PMID 23313912 DOI: 10.1038/nn.3309 |
0.577 |
|
| 2013 |
Macke JH, Murray I, Latham PE. Estimation bias in maximum entropy models Entropy. 15: 3109-3129. DOI: 10.3390/e15083209 |
0.414 |
|
| 2013 |
Macke J. Statistical Modelling of Psychophysical Data Perception. 42: 4-4. DOI: 10.1177/03010066130420S101 |
0.329 |
|
| 2012 |
Buesing L, Macke JH, Sahani M. Learning stable, regularised latent models of neural population dynamics. Network (Bristol, England). 23: 24-47. PMID 22663075 DOI: 10.3109/0954898X.2012.677095 |
0.71 |
|
| 2012 |
Schwartz G, Macke J, Amodei D, Tang H, Berry MJ. Low error discrimination using a correlated population code. Journal of Neurophysiology. 108: 1069-88. PMID 22539825 DOI: 10.1152/Jn.00564.2011 |
0.375 |
|
| 2012 |
Frund I, Wichmann F, Macke J. Dealing with sequential dependencies in psychophysical data Journal of Vision. 12: 1143-1143. DOI: 10.1167/12.9.1143 |
0.576 |
|
| 2012 |
Haefner RM, Gerwinn S, Macke JH, Bethge M. Inferring decoding strategy from choice probabilities in the presence of noise correlations Nature Precedings. 7: 1-1. DOI: 10.1038/Npre.2012.7014.1 |
0.577 |
|
| 2012 |
Buesing L, Macke JH, Sahani M. Spectral learning of linear dynamics from generalised-linear observations with application to neural population data Advances in Neural Information Processing Systems. 3. |
0.63 |
|
| 2011 |
Macke J, Berens P, Bethge M. Statistical analysis of multi-cell recordings: linking population coding models to experimental data. Frontiers in Computational Neuroscience. 5: 35. PMID 21847379 DOI: 10.3389/fncom.2011.00035 |
0.679 |
|
| 2011 |
Macke JH, Opper M, Bethge M. Common input explains higher-order correlations and entropy in a simple model of neural population activity. Physical Review Letters. 106: 208102. PMID 21668265 DOI: 10.1103/PhysRevLett.106.208102 |
0.6 |
|
| 2011 |
Gerwinn S, Macke JH, Bethge M. Reconstructing stimuli from the spike times of leaky integrate and fire neurons. Frontiers in Neuroscience. 5: 1. PMID 21390287 DOI: 10.3389/fnins.2011.00001 |
0.581 |
|
| 2011 |
Macke JH, Gerwinn S, White LE, Kaschube M, Bethge M. Gaussian process methods for estimating cortical maps. Neuroimage. 56: 570-81. PMID 20472075 DOI: 10.1016/J.Neuroimage.2010.04.272 |
0.537 |
|
| 2011 |
MacKe JH, Büsing L, Cunningham JP, Yu BM, Shenoy KV, Sahani M. Empirical models of spiking in neural populations Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. |
0.734 |
|
| 2010 |
Lyamzin DR, Macke JH, Lesica NA. Modeling Population Spike Trains with Specified Time-Varying Spike Rates, Trial-to-Trial Variability, and Pairwise Signal and Noise Correlations. Frontiers in Computational Neuroscience. 4: 144. PMID 21152346 DOI: 10.3389/fncom.2010.00144 |
0.403 |
|
| 2010 |
Macke JH, Wichmann FA. Estimating predictive stimulus features from psychophysical data: The decision image technique applied to human faces. Journal of Vision. 10: 22. PMID 20616129 DOI: 10.1167/10.5.22 |
0.603 |
|
| 2010 |
Gerwinn S, Macke JH, Bethge M. Bayesian inference for generalized linear models for spiking neurons. Frontiers in Computational Neuroscience. 4: 12. PMID 20577627 DOI: 10.3389/fncom.2010.00012 |
0.597 |
|
| 2010 |
Macke JH, Wichmann FA. Predicting psychophysical responses from stimulus features: A statistical evaluation of human gender categorization models Journal of Vision. 9: 519-519. DOI: 10.1167/9.8.519 |
0.581 |
|
| 2009 |
Gerwinn S, Macke J, Bethge M. Bayesian population decoding of spiking neurons. Frontiers in Computational Neuroscience. 3: 21. PMID 20011217 DOI: 10.3389/neuro.10.021.2009 |
0.608 |
|
| 2009 |
Macke JH, Berens P, Ecker AS, Tolias AS, Bethge M. Generating spike trains with specified correlation coefficients. Neural Computation. 21: 397-423. PMID 19196233 DOI: 10.1162/Neco.2008.02-08-713 |
0.772 |
|
| 2009 |
Macke JH, Gerwinn S, White LE, Kaschube M, Bethge M. Bayesian estimation of orientation preference maps Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1195-1203. DOI: 10.3389/Conf.Neuro.06.2009.03.310 |
0.477 |
|
| 2009 |
Gerwinn S, MacKe JH, Seeger M, Bethge M. Bayesian inference for spiking neuron models with a sparsity prior Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. |
0.513 |
|
| 2009 |
MacKe JH, Zeck G, Bethge M. Receptive fields without spike-triggering Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. |
0.431 |
|
| 2008 |
Ku SP, Gretton A, Macke J, Logothetis NK. Comparison of pattern recognition methods in classifying high-resolution BOLD signals obtained at high magnetic field in monkeys. Magnetic Resonance Imaging. 26: 1007-14. PMID 18691999 DOI: 10.1016/j.mri.2008.02.016 |
0.34 |
|
| 2008 |
Macke JH, Maack N, Gupta R, Denk W, Schölkopf B, Borst A. Contour-propagation algorithms for semi-automated reconstruction of neural processes. Journal of Neuroscience Methods. 167: 349-57. PMID 17870180 DOI: 10.1016/j.jneumeth.2007.07.021 |
0.532 |
|
| 2007 |
Bethge M, Gerwinn S, Macke JH. Unsupervised learning of a steerable basis for invariant image representations Proceedings of Spie - the International Society For Optical Engineering. 6492. DOI: 10.1117/12.711119 |
0.428 |
|
| 2007 |
Laub J, MacKe J, Müller KR, Wichmann FA. Inducing metric violations in human similarity judgements Advances in Neural Information Processing Systems. 777-784. |
0.587 |
|
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